Diabetic kidney disease (DKD) occurs in 25%-40% of patients with diabetes. Given the dual problems of a significant risk of progression from DKD to end-stage renal disease (ESRD) and increased ...cardiovascular morbidity and mortality, it is important to identify patients at risk of DKD and ESRD and initiate protective renal and cardiovascular therapies. The importance of preventive therapy is emphasized further by worldwide increases in the incidence of diabetes. This review summarizes the evidence regarding the prognostic value and benefits of targeting established and novel risk markers for DKD development and progression. Family history of DKD, smoking history, and glycemic, blood pressure, and plasma lipid level control are established factors for identifying people at greatest risk of DKD development and progression. Absolute albumin excretion rate (AER) and glomerular filtration rate (GFR) measurements also are important, although AER categorization generally lacks the necessary specificity and sensitivity, and estimates of declining GFR are compromised by methodological limitations for GFRs in the normal-to-high range. Emerging risk markers for progressive loss of kidney function include markers of oxidation and inflammation, profibrotic cytokines, uric acid, advanced glycation end products, functional and structural markers of vascular dysfunction, kidney structural changes, and tubular biomarkers. Among these, the most promising are serum uric acid and soluble tumor necrosis factor receptor (type 1 and type 2) levels, especially in relation to GFR changes. At present, these can only be considered as risk markers because they only identify an individual at increased risk of progressive DKD and not necessarily related to the causal pathway promoting kidney damage. Further work is needed to establish whether modulating these factors improves the prognosis in DKD. Although change in urinary peptidome levels also is a promising marker, there currently is neither a clinical assay nor adequate studies defining its prognostic value. Until these or other novel markers become available for clinical use, predictive accuracy often may be increased with greater attention to established markers.
The purpose of this study is to evaluate the feasibility and patient acceptability of a novel artificial intelligence (AI)-based diabetic retinopathy (DR) screening model within endocrinology ...outpatient settings. Adults with diabetes were recruited from two urban endocrinology outpatient clinics and single-field, non-mydriatic fundus photographs were taken and graded for referable DR ( ≥ pre-proliferative DR). Each participant underwent; (1) automated screening model; where a deep learning algorithm (DLA) provided real-time reporting of results; and (2) manual model where retinal images were transferred to a retinal grading centre and manual grading outcomes were distributed to the patient within 2 weeks of assessment. Participants completed a questionnaire on the day of examination and 1-month following assessment to determine overall satisfaction and the preferred model of care. In total, 96 participants were screened for DR and the mean assessment time for automated screening was 6.9 minutes. Ninety-six percent of participants reported that they were either satisfied or very satisfied with the automated screening model and 78% reported that they preferred the automated model over manual. The sensitivity and specificity of the DLA for correct referral was 92.3% and 93.7%, respectively. AI-based DR screening in endocrinology outpatient settings appears to be feasible and well accepted by patients.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Abstract
Context
Diabetic ketoacidosis (DKA) has been associated with the use of sodium glucose cotransporter 2 inhibitors (SGLT2is).
Objective
To determine the incidence, characteristics, and ...outcomes of DKA in SGLT2i users vs nonusers with type 2 diabetes.
Design
Retrospective, multicenter, controlled cohort study.
Setting
All public hospitals in Melbourne and Geelong (combined population of 5 million), Australia, from 1 September 2015 to 31 October 2017.
Patients
Consecutive cases of DKA that developed in the community, or during the course of hospital admission, in patients with type 2 diabetes
Main Outcome Measures
In SGLT2i users vs nonusers: (i) OR of DKA developing during hospital admission, and (ii) incidence of DKA.
Results
There were 162 cases of DKA (37 SGLT2i users and 125 non-SGLT2i users) with a physician-adjudicated diagnosis of type 2 diabetes. Of these, DKA developed during the course of inpatient admission in 14 (38%) SGLT2i users vs 2 (2%) non-SGLT2i users (OR, 37.4; 95% CI, 8.0 to 175.9; P < 0.0001). The incidence of DKA was 1.02 per 1000 (95% CI, 0.74 to 1.41 per 1000) in SGLT2i users vs 0.69 per 1000 (95% CI, 0.58 to 0.82 per 1000) in non-SGLT2i users (OR, 1.48; 95% CI, 1.02 to 2.15; P = 0.037). Fifteen SGLT2i users (41%) had peak blood glucose <250 mg/dL (14 mmol/L) compared with one (0.8%) non-SGLT2i user (P < 0.001).
Conclusions
SGLT2i users were more likely to develop DKA as an inpatient compared with non-SGLT2i users. SGLT2i use was associated with a small but significant increased risk of DKA.
During the course of hospital admission, diabetic ketoacidosis developed more frequently in SGLT2 inhibitor users vs nonusers, with an OR of 37.4 (95% CI, 8.0 to 175.9; P < 0.0001).
Diabetic kidney disease (DKD) represents a major component of the health burden associated with type 1 and type 2 diabetes. Recent advances have produced an explosion of ‘novel’ assay‐based risk ...markers for DKD, though clinical use remains restricted. Although many patients with progressive DKD follow a classical albuminuria‐based pathway, non‐albuminuric DKD progression is now well recognized. In general, the following clinical and biochemical characteristics have been associated with progressive DKD in both type 1 and type 2 diabetes: increased hemoglobin A1c, systolic blood pressure, albuminuria grade, early glomerular filtration rate decline, duration of diabetes, age (including pubertal onset) and serum uric acid; the presence of concomitant microvascular complications; and positive family history. The same is true in type 2 diabetes for male sex category, in patients following an albuminuric pathway to DKD, and also true for the presence of increased pulse wave velocity. The following baseline clinical characteristics have been proposed as risk factors for DKD progression, but with further research required to assess the nature of any relationship: dyslipidemia (including low‐density lipoprotein, total and high‐density lipoprotein cholesterol); elevated body mass index; smoking status; hyperfiltration; decreases in vitamin D, hemoglobin and uric acid excretion (all known consequences of advanced DKD); and patient test result visit‐to‐visit variability (hemoglobin A1c, blood pressure and high‐density lipoprotein cholesterol). The development of multifactorial ‘renal risk equations’ for type 2 diabetes has the potential to simplify the task of DKD prognostication; however, there are currently none for type 1 diabetes‐specific populations. Significant progress has been made in the prediction of DKD progression using readily available clinical data, though further work is required to elicit the role of several variables, and to consolidate data to facilitate clinical implementation.
Diabetic Kidney Disease represents a major component of the health burden associated with type 1 and type 2 diabetes. This article summarises clinical variables associated with the progression of Diabetic Kidney Disease; a brief discussion is also made of promising ‘novel’ biomarkers which may eventually become readily available to the practicing clinician.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
To assess the efficacy and safety of closed-loop insulin delivery compared with sensor-augmented pump therapy among older adults with type 1 diabetes.
This open-label, randomized (1:1), crossover ...trial compared 4 months of closed-loop versus sensor-augmented pump therapy. Eligible adults were aged ≥60 years, with type 1 diabetes (duration ≥10 years), using an insulin pump. The primary outcome was continuous glucose monitoring (CGM) time in range (TIR; 3.9-10.0 mmol/L).
There were 30 participants (mean age 67 SD 5 years), with median type 1 diabetes duration of 38 years (interquartile range IQR 20-47), randomized (n = 15 to each sequence); all completed the trial. The mean TIR was 75.2% (SD 6.3) during the closed-loop stage and 69.0% (9.1) during the sensor-augmented pump stage (difference of 6.2 percentage points 95% CI 4.4 to 8.0; P < 0.0001). All prespecified CGM metrics favored closed loop over the sensor-augmented pump; benefits were greatest overnight. Closed loop reduced CGM time <3.9 mmol/L during 24 h/day by 0.5 percentage points (95% CI 0.3 to 1.1; P = 0.0005) and overnight by 0.8 percentage points (0.4 to 1.1; P < 0.0001) compared with sensor-augmented pump. There was no significant difference in HbA1c between closed-loop versus sensor-augmented pump stages (7.3% IQR, 7.1-7.5 (56 mmol/mol 54-59) vs. 7.5% 7.1-7.9 (59 mmol/mol 54-62), respectively; P = 0.13). Three severe hypoglycemia events occurred during the closed-loop stage and two occurred during the sensor-augmented pump stage; no hypoglycemic events required hospitalization. One episode of diabetic ketoacidosis occurred during the sensor-augmented pump stage; no serious adverse events occurred during the closed-loop stage.
Closed-loop therapy is an effective treatment option for older adults with long-duration type 1 diabetes, and no safety issues were identified. These older adults had higher TIR accompanied by less time below range during closed loop than during sensor-augmented pump therapy. Of particular clinical importance, closed loop reduced the time spent in hypoglycemic range overnight.
Diabetic nephropathy (DN) is a progressive kidney disease, a well-known complication of long-standing diabetes. DN is the most frequent reason for dialysis in many Western countries. Early detection ...may enable development of specific drugs and early initiation of therapy, thereby postponing/preventing the need for renal replacement therapy. We evaluated urinary proteome analysis as a tool for prediction of DN. Capillary electrophoresis-coupled mass spectrometry was used to profile the low-molecular weight proteome in urine. We examined urine samples from a longitudinal cohort of type 1 and 2 diabetic patients (n = 35) using a previously generated chronic kidney disease (CKD) biomarker classifier to assess peptides of collected urines for signs of DN. The application of this classifier to samples of normoalbuminuric subjects up to 5 years prior to development of macroalbuminuria enabled early detection of subsequent progression to macroalbuminuria (area under the curve AUC 0.93) compared with urinary albumin routinely used to determine the diagnosis (AUC 0.67). Statistical analysis of each urinary CKD biomarker depicted its regulation with respect to diagnosis of DN over time. Collagen fragments were prominent biomarkers 3-5 years before onset of macroalbuminuria. Before albumin excretion starts to increase, there is a decrease in collagen fragments. Urinary proteomics enables noninvasive assessment of DN risk at an early stage via determination of specific collagen fragments.
The reasons for reduced exercise capacity in diabetes mellitus (DM) remains incompletely understood, although diastolic dysfunction and diabetic cardiomyopathy are often favored explanations. ...However, there is a paucity of literature detailing cardiac function and reserve during incremental exercise to evaluate its significance and contribution. We sought to determine associations between comprehensive measures of cardiac function during exercise and maximal oxygen consumption (Formula: see textpeak), with the hypothesis that the reduction in exercise capacity and cardiac function would be associated with co-morbidities and sedentary behavior rather than diabetes itself.
This case-control study involved 60 subjects 20 with type 1 DM (T1DM), 20 T2DM, and 10 healthy controls age/sex-matched to each diabetes subtype performing cardiopulmonary exercise testing and bicycle ergometer echocardiography studies. Measures of biventricular function were assessed during incremental exercise to maximal intensity.
T2DM subjects were middle-aged (52 ± 11 years) with a mean T2DM diagnosis of 12 ± 7 years and modest glycemic control (HbA
57 ± 12 mmol/mol). T1DM participants were younger (35 ± 8 years), with a 19 ± 10 year history of T1DM and suboptimal glycemic control (HbA
65 ± 16 mmol/mol). Participants with T2DM were heavier than their controls (body mass index 29.3 ± 3.4 kg/m
vs. 24.7 ± 2.9, P = 0.001), performed less exercise (10 ± 12 vs. 28 ± 30 MET hours/week, P = 0.031) and had lower exercise capacity (Formula: see textpeak = 26 ± 6 vs. 38 ± 8 ml/min/kg, P < 0.0001). These differences were not associated with biventricular systolic or left ventricular (LV) diastolic dysfunction at rest or during exercise. There was no difference in weight, exercise participation or Formula: see textpeak in T1DM subjects as compared to their controls. After accounting for age, sex and body surface area in a multivariate analysis, significant positive predictors of Formula: see textpeak were cardiac size (LV end-diastolic volume, LVEDV) and estimated MET-hours, while T2DM was a negative predictor. These combined factors accounted for 80% of the variance in Formula: see textpeak (P < 0.0001).
Exercise capacity is reduced in T2DM subjects relative to matched controls, whereas exercise capacity is preserved in T1DM. There was no evidence of sub-clinical cardiac dysfunction but, rather, there was an association between impaired exercise capacity, small LV volumes and sedentary behavior.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
PURPOSE OF REVIEWHistorically, for people at risk of developing diabetic chronic kidney disease (CKD), an initial increase in albumin excretion rate (AER) has been linked to a subsequent decline in ...glomerular filtration rate (GFR). We review recent findings that suggest that in some people with diabetic CKD there is an uncoupling of progressive increases in AER and declining GFR.
RECENT FINDINGSApproximately 20% of people with type 2 diabetes develop at least stage 3 CKD, defined as an estimated GFR (eGFR) less than 60 ml/min/1.73 m, after accounting for the use of renin–angiotensin system blockers, while remaining normoalbuminuric. A recent analysis from the Diabetes Control and Complications Trial and Epidemiology of Diabetes Interventions and Complications study has shown that 24% of people with type 1 diabetes reached an eGFR threshold of less than 60 ml/min/1.73 m that was not associated with a rise in albuminuria to the microalbuminuria or macroalbuminuria range. This discordance between changes in GFR and AER has resulted in a search for new markers that identify people with diabetes who are at risk of declining GFR independent of progressive increases in AER.
SUMMARYThe conventional paradigm of kidney disease in people with diabetes has been challenged. Changes in AER and GFR are being increasingly recognized as complementary rather than obligatory manifestations of diabetic CKD.
The concept of microalbuminuria has been central to the development of clinical practice and research in the area of diabetic kidney disease (DKD). However, in recent times, the value of a paradigm ...of DKD based solely on microalbuminuria has been questioned. Although both the absolute level and rate of change of microalbuminuria are linked to the development and progression of DKD, microalbuminuria on its own lacks the necessary sensitivity or specificity to accurately predict kidney outcomes for people with diabetes. The development of microalbumiuria can no longer be viewed as a committed and irreversible stage of DKD, as spontaneous remission is now reported as a common occurrence. In addition, the absence of microalbuminuria or its progression to proteinuria does not signify that an individual patient is safe from a progressive decline in glomerular filtration rate (GFR). Furthermore, although reductions in albuminuria within the microalbuminuric range can be linked to a slower GFR decline in observational studies, this relationship has not been robustly demonstrated in intervention studies. Conclusions regarding the kidney health of individuals with diabetes will continue to be flawed if an inappropriate emphasis is placed on the presence or absence of albuminuria or changes in albuminuria within the microalbuminuric range. This has important implications in terms of undermining the value of microalbuminuria as a surrogate renal end point for intervention trials. There is a need to develop broader models of progressive DKD that include novel pathways and risk markers apart from those related to the traditional ‘albuminuric pathway’ to renal impairment.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Accumulation of advanced glycation endproducts (AGEs) is linked to decline in renal function, particularly in patients with diabetes. Major forms of AGEs in serum are protein-bound AGEs and AGE free ...adducts. In this study, we assessed levels of AGEs in subjects with and without diabetes, with normal renal function and stages 2 to 4 chronic kidney disease (CKD), to identify which AGE has the greatest progressive change with decline in renal function and change in diabetes. We performed a cross-sectional study of patients with stages 2-4 CKD, with and without diabetes, and healthy controls (
= 135). Nine protein-bound and free adduct AGEs were quantified in serum. Most protein-bound AGEs increased moderately through stages 2-4 CKD whereas AGE free adducts increased markedly. Methylglyoxal-derived hydroimidazolone MG-H1 free adduct was the AGE most responsive to CKD status, increasing 8-fold and 30-fold in stage 4 CKD in patients without and with diabetes, respectively. MG-H1 Glomerular filtration flux was increased 5-fold in diabetes, likely reflecting increased methylglyoxal glycation status. We conclude that serum MG-H1 free adduct concentration was strongly related to stage of CKD and increased in diabetes status. Serum MG-H1 free adduct is a candidate AGE risk marker of non-diabetic and diabetic CKD.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
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